The core problem is that the deployed recommendation model is attempting to model the underlying user preferences, making it difficult to make claims about user behaviour (or use the behaviour data) without accounting for algorithmic confounding [1]}, [2]}.
On the other hand, if the RecSys component in Figure REF  is a random model, then the interconnection between the User and the RecSys components blackin Figure REF  will be removed and the RecSys component has no effect on the collected feedback dataset, blacka situation known as open loop feedback, i.e. no item blackreceives more or less expected exposure compared to any other item in the collection [3]}.
